Federation of Data Governance Areas in a Data Mesh Architecture
Lågland, Tony (2024)
2024
Tietojohtamisen DI-ohjelma - Master's Programme in Information and Knowledge Management
Johtamisen ja talouden tiedekunta - Faculty of Management and Business
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Hyväksymispäivämäärä
2024-05-19
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:tuni-202405135794
https://urn.fi/URN:NBN:fi:tuni-202405135794
Tiivistelmä
The amount of data used by companies has grown and the rate is only increasing. Many of the current, often highly centralized, data architectures rely on older concepts which are not scaling at the same rate than the amounts of data. To answer these issues presented by older architectures and growing amounts of data, the concept of data mesh was created.
Data mesh is still a rather new concept and has not been researched that much. When talking about data architectures and data in general, one important factor is data governance. In data mesh related literature data governance is said to be federated, but currently there is not much literature or research on how it federates. This thesis aims to research the topic further.
The research began by establishing a list of key data governance areas according to literature. The level of federation of these individual areas was then researched by conducting interviews for data governance and data architecture professionals.
The results for this thesis are presented in table format containing information on the level of federation for each data governance area as well as key themes affecting the level of federation. On general level, the findings were that most of the data governance areas will federate, but for most there is a need for centralized support. The results were mostly not unambiguous, which means the data governance area can be either highly centralized or decentralized depending on the organization. For most of these areas the level of federation was highly dependent on organizational context. Organizations operating in a highly regulated area will most likely have less federated and more centralized data governance. Still, to be able to benefit from data mesh, federation is needed.
This thesis assists organizations in implementing a data governance structure suitable for a data mesh architecture. Additionally, this thesis gives insight on what factors affect the federation of individual data governance areas.
Data mesh is still a rather new concept and has not been researched that much. When talking about data architectures and data in general, one important factor is data governance. In data mesh related literature data governance is said to be federated, but currently there is not much literature or research on how it federates. This thesis aims to research the topic further.
The research began by establishing a list of key data governance areas according to literature. The level of federation of these individual areas was then researched by conducting interviews for data governance and data architecture professionals.
The results for this thesis are presented in table format containing information on the level of federation for each data governance area as well as key themes affecting the level of federation. On general level, the findings were that most of the data governance areas will federate, but for most there is a need for centralized support. The results were mostly not unambiguous, which means the data governance area can be either highly centralized or decentralized depending on the organization. For most of these areas the level of federation was highly dependent on organizational context. Organizations operating in a highly regulated area will most likely have less federated and more centralized data governance. Still, to be able to benefit from data mesh, federation is needed.
This thesis assists organizations in implementing a data governance structure suitable for a data mesh architecture. Additionally, this thesis gives insight on what factors affect the federation of individual data governance areas.